ML.NET Revealed
Apress (Verlag)
978-1-4842-6542-0 (ISBN)
Dive in to learn how ML.NET is designed to encapsulate complex algorithms, making it easy to consume them in many application settings without having to think about the internal details. You will learn about the features that do the necessary “plumbing” that is required in a variety of machine learning problems, freeing up your time to focus on your applications. You will understand that while the infrastructure pieces may at first appear to be disconnected and haphazard, they are not.
Developers who are curious about trying machine learning, yet are shying away from it due to its perceived complexity, will benefit from this book. This introductory guide will help you make sense of it all and inspire you to try outscenarios and code samples that can be used in many real-world situations.
What You Will Learn
Create a machine learning model using only the C# language
Build confidence in your understanding of machine learning algorithms
Painlessly implement algorithms
Begin using the ML.NET library software
Recognize the many opportunities to utilize ML.NET to your advantage
Apply and reuse code samples from the book
Utilize the bonus algorithm selection quick references available online
Who This Book Is For
Developers who want to learn how to use and apply machine learning to enrich their applications
Sudipta Mukherjee is an electronics engineer by education and a computer scientist by profession. He holds a degree in electronics and communication engineering. He is passionate about data structure, algorithms, text processing, natural language processing tools development, programming languages, and machine learning. He is the author of several technical books. He has presented at @FuConf and other developer events, and he lives in Bangalore with his wife and son.
Chapter 1: Meet ML.NET.- Chapter 2: The Pipeline.- Chapter 3: Handling Data.- Chapter 4: Regressions.- Chapter 5: Classifications.- Chapter 6: Clustering.- Chapter 7: Sentiment Analysis.- Chapter 8: Product Recommendation.- Chapter 9: Anomaly Detection.- Chapter 10: Object Detection.
| Erscheinungsdatum | 14.01.2021 |
|---|---|
| Zusatzinfo | 160 Illustrations, black and white; XVIII, 174 p. 160 illus. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Software Entwicklung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | C# • deep learning framworks • Deep learning models • machine learning • machine learning algorithms • machine learning and Onxx • machine learning and TensorFlow • Microsoft Machine Learning • ML Models • ML.NET • .NET • Python |
| ISBN-10 | 1-4842-6542-4 / 1484265424 |
| ISBN-13 | 978-1-4842-6542-0 / 9781484265420 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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